Sentence Similarity
sentence-transformers
ONNX
Safetensors
bert
feature-extraction
gte
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use Mihaiii/Ivysaur with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Mihaiii/Ivysaur with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Mihaiii/Ivysaur") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Mihaiii/Ivysaur: direct link, hf CLI and curl.
- Browser
- Download file 90.9 MB
-
https://huggingface.co/Mihaiii/Ivysaur/resolve/main/model.safetensors
- Command line
-
hf download hf://Mihaiii/Ivysaur/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Mihaiii/Ivysaur/resolve/main/model.safetensors
90.9 MB
- Xet hash:
- 84995f079da2fdda55ac588a70ad3df640d75f20f0b9c5b307d4b75164c57d1d
- Size of remote file:
- 90.9 MB
- SHA256:
- 330415ca953730e98bfa032eb80889bcf76fb02b228e8ecc82af0174df0769be
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